Lapped nonlinear interpolative vector quantization and image super-resolution

Author

Sheppard, David G. ; Panchapakesan, Kannan ; Bilgin, Ali ; Hunt, Bobby R. ; Marcellin, Michael W.

Author_Institution

Dept. of Electr. & Comput. Eng., Arizona Univ., Tucson, AZ, USA

Volume

9

Issue

2

fYear

2000

fDate

2/1/2000 12:00:00 AM

Firstpage

295

Lastpage

298

Abstract

This article presents an improved version of an algorithm designed to perform image restoration via nonlinear interpolative vector quantization (NLIVQ). The improvement results from using lapped blocks during the decoding process. The algorithm is trained on original and diffraction-limited image pairs. The discrete cosine transform is again used in the codebook design process to control complexity. Simulation results are presented which demonstrate improvements over the nonlapped algorithm in both observed image quality and peak signal-to-noise ratio. In addition, the nonlinearity of the algorithm is shown to produce super-resolution in the restored images

Keywords

decoding; discrete cosine transforms; image coding; image resolution; image restoration; interpolation; transform coding; vector quantisation; NLIVQ; algorithm training; codebook design; complexity control; decoding; diffraction-limited image pairs; discrete cosine transform; image quality; image restoration; image super-resolution; lapped blocks; lapped nonlinear interpolative vector quantization; nonlapped algorithm; nonlinear algorithm; nonlinearity; peak signal-to-noise ratio; simulation results; Algorithm design and analysis; Decoding; Diffraction; Discrete cosine transforms; Image quality; Image restoration; PSNR; Process control; Process design; Vector quantization;

fLanguage

English

Journal_Title

Image Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7149

Type

jour

DOI

10.1109/83.821746

Filename

821746